Application of Experimental Design for Probabilistic IOR Evaluation at Korolev Field

Abstract

Tengizchevroil (TCO) is the biggest operator in Kazakhstan developing two world's deepest supergiant oilfields - Tengiz and, its satellite field, Korolev. With over 20 years of oil production at TCO, reservoir pressure has been declining and is approaching bubble point pressure. In order to arrest the declining pressure trend and extend oil production plateau, TCO is evaluating Improved Oil Recovery (IOR) opportunities, including potential Waterflood in Korolev field. Accurate Waterflood evaluation requires improved characterization of the main uncertainties impacting ultimate recovery under IOR processes. Therefore, we built next-generation Korolev reservoir model (SIM15K) which incorporates results of the latest characterization efforts based on the latest wide- azimuth 3D seismic survey. This work led to updated Korolev depositional model, which helps to understand the links between geological settings and fracture occurrence. In conjunction with the first implementation of Dynamic Data Integration workflow, this resulted into updated Low-Mid-High fracture models - one of the main factors controlling Waterflood performance in naturally-fractured reservoirs. This paper focuses on Brownfield Experimental Design (ED) of Korolev field, which is specifically designed to provide an estimate of IOR Incremental Recovery. We identified 23 main uncertainty parameters for each Low-Mid-High Fracture models. The Brownfield ED was run with two development scenarios: Primary Depletion and Waterflood to get probabilistic assessment of Incremental Waterflood Recovery. Overall 803 cases were required for each fracture model and development scenario to generate good quality proxies for cumulative recoveries and History-Match error. Those proxies were used to sample the entire space of uncertainties and define P10/50/90 targets. As a result of robust Brownfield ED, we selected P10/50/90 models to capture both range in Incremental Waterflood Recovery and Ultimate Recovery under Primary Depletion. The underlying uncertainty parameters for the final model selection were picked based on their relative impact on the objective functions. Currently, the new SIM15K model is being used for Korolev Waterflood evaluation and optimization, Reserves estimation, existing infrastructure optimization and future projects design.